Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality
Cellular metabolism plays a role in the observed variability of a drug substance's Critical Quality Attributes (CQAs) made by biomanufacturing processes. Therefore, here we describe a new approach for monitoring biomanufacturing processes that measures a set of metabolic reaction rates (named C...
Gespeichert in:
Veröffentlicht in: | Biotechnology and bioengineering 2024-10 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | Biotechnology and bioengineering |
container_volume | |
creator | Bush, Xin Fratz-Berilla, Erica J Kohnhorst, Casey L King, Roberta Agarabi, Cyrus Powers, David N Trunfio, Nicholas |
description | Cellular metabolism plays a role in the observed variability of a drug substance's Critical Quality Attributes (CQAs) made by biomanufacturing processes. Therefore, here we describe a new approach for monitoring biomanufacturing processes that measures a set of metabolic reaction rates (named Critical Metabolic Parameters (CMP) in addition to the macroscopic process conditions currently being used as Critical Process Parameters (CPP) for biomanufacturing. Constraint-based systems biology models like Flux Balance Analysis (FBA) are used to estimate metabolic reaction rates, and metabolic rates are used as inputs for multivariate Batch Evolution Models (BEM). Metabolic activity was reproducible among batches and could be monitored to detect a deliberately induced macroscopic process shift (i.e., temperature change). The CMP approach has the potential to enable "golden batches" in biomanufacturing processes to be defined from the internal metabolic activity and to aid in detecting process changes that may impact the quality of the product. Overall, the data suggested that monitoring of metabolic activity has promise for biomanufacturing process control. |
doi_str_mv | 10.1002/bit.28873 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3121280450</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3121280450</sourcerecordid><originalsourceid>FETCH-LOGICAL-c175t-7837d67579661759b0af08b10407e75752b2455f65998fdfd6275be7aee8cdb43</originalsourceid><addsrcrecordid>eNo9kc1OxCAUhYnR6Di68AUMS11UKS1QluOMf8kYNdF1Q-nFwbRFgZrMW_jIoo6u7t93zuIehI5ycpYTQs8bG89oVYliC01yIkVGqCTbaEII4VnBJN1D-yG8plFUnO-ivUKWnEohJuhzAcYOdnjB165rYcAXKuoVBGxTa12vhtEoHUf_jTx4pyGEdL3yrse3QwQ_qA7fQVSN66zGMx3th41rHB1eQAQd_0R4vlLDS5I-rVTEd2qNZ8Zs7u2Y6uOouqQ8QDtGdQEON3WKnq8un-Y32fL--nY-W2Y6FyxmoipEywUTkvO0kA1RhlRNTkoiIK0ZbWjJmOFMysq0puVUsAaEAqh025TFFJ38-r559z5CiHVvg4auUwO4MdRFTnNakZKRhJ7-otq7EDyY-s3bXvl1nZP6O4A6BVD_BJDY443t2PTQ_pN_Hy--AINrghU</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3121280450</pqid></control><display><type>article</type><title>Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality</title><source>Wiley Online Library All Journals</source><creator>Bush, Xin ; Fratz-Berilla, Erica J ; Kohnhorst, Casey L ; King, Roberta ; Agarabi, Cyrus ; Powers, David N ; Trunfio, Nicholas</creator><creatorcontrib>Bush, Xin ; Fratz-Berilla, Erica J ; Kohnhorst, Casey L ; King, Roberta ; Agarabi, Cyrus ; Powers, David N ; Trunfio, Nicholas</creatorcontrib><description>Cellular metabolism plays a role in the observed variability of a drug substance's Critical Quality Attributes (CQAs) made by biomanufacturing processes. Therefore, here we describe a new approach for monitoring biomanufacturing processes that measures a set of metabolic reaction rates (named Critical Metabolic Parameters (CMP) in addition to the macroscopic process conditions currently being used as Critical Process Parameters (CPP) for biomanufacturing. Constraint-based systems biology models like Flux Balance Analysis (FBA) are used to estimate metabolic reaction rates, and metabolic rates are used as inputs for multivariate Batch Evolution Models (BEM). Metabolic activity was reproducible among batches and could be monitored to detect a deliberately induced macroscopic process shift (i.e., temperature change). The CMP approach has the potential to enable "golden batches" in biomanufacturing processes to be defined from the internal metabolic activity and to aid in detecting process changes that may impact the quality of the product. Overall, the data suggested that monitoring of metabolic activity has promise for biomanufacturing process control.</description><identifier>ISSN: 0006-3592</identifier><identifier>ISSN: 1097-0290</identifier><identifier>EISSN: 1097-0290</identifier><identifier>DOI: 10.1002/bit.28873</identifier><identifier>PMID: 39462977</identifier><language>eng</language><publisher>United States</publisher><ispartof>Biotechnology and bioengineering, 2024-10</ispartof><rights>2024 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c175t-7837d67579661759b0af08b10407e75752b2455f65998fdfd6275be7aee8cdb43</cites><orcidid>0000-0002-9259-0540 ; 0000-0002-5568-5938</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39462977$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bush, Xin</creatorcontrib><creatorcontrib>Fratz-Berilla, Erica J</creatorcontrib><creatorcontrib>Kohnhorst, Casey L</creatorcontrib><creatorcontrib>King, Roberta</creatorcontrib><creatorcontrib>Agarabi, Cyrus</creatorcontrib><creatorcontrib>Powers, David N</creatorcontrib><creatorcontrib>Trunfio, Nicholas</creatorcontrib><title>Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality</title><title>Biotechnology and bioengineering</title><addtitle>Biotechnol Bioeng</addtitle><description>Cellular metabolism plays a role in the observed variability of a drug substance's Critical Quality Attributes (CQAs) made by biomanufacturing processes. Therefore, here we describe a new approach for monitoring biomanufacturing processes that measures a set of metabolic reaction rates (named Critical Metabolic Parameters (CMP) in addition to the macroscopic process conditions currently being used as Critical Process Parameters (CPP) for biomanufacturing. Constraint-based systems biology models like Flux Balance Analysis (FBA) are used to estimate metabolic reaction rates, and metabolic rates are used as inputs for multivariate Batch Evolution Models (BEM). Metabolic activity was reproducible among batches and could be monitored to detect a deliberately induced macroscopic process shift (i.e., temperature change). The CMP approach has the potential to enable "golden batches" in biomanufacturing processes to be defined from the internal metabolic activity and to aid in detecting process changes that may impact the quality of the product. Overall, the data suggested that monitoring of metabolic activity has promise for biomanufacturing process control.</description><issn>0006-3592</issn><issn>1097-0290</issn><issn>1097-0290</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNo9kc1OxCAUhYnR6Di68AUMS11UKS1QluOMf8kYNdF1Q-nFwbRFgZrMW_jIoo6u7t93zuIehI5ycpYTQs8bG89oVYliC01yIkVGqCTbaEII4VnBJN1D-yG8plFUnO-ivUKWnEohJuhzAcYOdnjB165rYcAXKuoVBGxTa12vhtEoHUf_jTx4pyGEdL3yrse3QwQ_qA7fQVSN66zGMx3th41rHB1eQAQd_0R4vlLDS5I-rVTEd2qNZ8Zs7u2Y6uOouqQ8QDtGdQEON3WKnq8un-Y32fL--nY-W2Y6FyxmoipEywUTkvO0kA1RhlRNTkoiIK0ZbWjJmOFMysq0puVUsAaEAqh025TFFJ38-r559z5CiHVvg4auUwO4MdRFTnNakZKRhJ7-otq7EDyY-s3bXvl1nZP6O4A6BVD_BJDY443t2PTQ_pN_Hy--AINrghU</recordid><startdate>20241027</startdate><enddate>20241027</enddate><creator>Bush, Xin</creator><creator>Fratz-Berilla, Erica J</creator><creator>Kohnhorst, Casey L</creator><creator>King, Roberta</creator><creator>Agarabi, Cyrus</creator><creator>Powers, David N</creator><creator>Trunfio, Nicholas</creator><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9259-0540</orcidid><orcidid>https://orcid.org/0000-0002-5568-5938</orcidid></search><sort><creationdate>20241027</creationdate><title>Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality</title><author>Bush, Xin ; Fratz-Berilla, Erica J ; Kohnhorst, Casey L ; King, Roberta ; Agarabi, Cyrus ; Powers, David N ; Trunfio, Nicholas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c175t-7837d67579661759b0af08b10407e75752b2455f65998fdfd6275be7aee8cdb43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bush, Xin</creatorcontrib><creatorcontrib>Fratz-Berilla, Erica J</creatorcontrib><creatorcontrib>Kohnhorst, Casey L</creatorcontrib><creatorcontrib>King, Roberta</creatorcontrib><creatorcontrib>Agarabi, Cyrus</creatorcontrib><creatorcontrib>Powers, David N</creatorcontrib><creatorcontrib>Trunfio, Nicholas</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Biotechnology and bioengineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bush, Xin</au><au>Fratz-Berilla, Erica J</au><au>Kohnhorst, Casey L</au><au>King, Roberta</au><au>Agarabi, Cyrus</au><au>Powers, David N</au><au>Trunfio, Nicholas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality</atitle><jtitle>Biotechnology and bioengineering</jtitle><addtitle>Biotechnol Bioeng</addtitle><date>2024-10-27</date><risdate>2024</risdate><issn>0006-3592</issn><issn>1097-0290</issn><eissn>1097-0290</eissn><abstract>Cellular metabolism plays a role in the observed variability of a drug substance's Critical Quality Attributes (CQAs) made by biomanufacturing processes. Therefore, here we describe a new approach for monitoring biomanufacturing processes that measures a set of metabolic reaction rates (named Critical Metabolic Parameters (CMP) in addition to the macroscopic process conditions currently being used as Critical Process Parameters (CPP) for biomanufacturing. Constraint-based systems biology models like Flux Balance Analysis (FBA) are used to estimate metabolic reaction rates, and metabolic rates are used as inputs for multivariate Batch Evolution Models (BEM). Metabolic activity was reproducible among batches and could be monitored to detect a deliberately induced macroscopic process shift (i.e., temperature change). The CMP approach has the potential to enable "golden batches" in biomanufacturing processes to be defined from the internal metabolic activity and to aid in detecting process changes that may impact the quality of the product. Overall, the data suggested that monitoring of metabolic activity has promise for biomanufacturing process control.</abstract><cop>United States</cop><pmid>39462977</pmid><doi>10.1002/bit.28873</doi><orcidid>https://orcid.org/0000-0002-9259-0540</orcidid><orcidid>https://orcid.org/0000-0002-5568-5938</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0006-3592 |
ispartof | Biotechnology and bioengineering, 2024-10 |
issn | 0006-3592 1097-0290 1097-0290 |
language | eng |
recordid | cdi_proquest_miscellaneous_3121280450 |
source | Wiley Online Library All Journals |
title | Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T19%3A01%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Defining%20Golden%20Batches%20in%20Biomanufacturing%20Processes%20From%20Internal%20Metabolic%20Activity%20to%20Detect%20Process%20Changes%20That%20May%20Affect%20Product%20Quality&rft.jtitle=Biotechnology%20and%20bioengineering&rft.au=Bush,%20Xin&rft.date=2024-10-27&rft.issn=0006-3592&rft.eissn=1097-0290&rft_id=info:doi/10.1002/bit.28873&rft_dat=%3Cproquest_cross%3E3121280450%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3121280450&rft_id=info:pmid/39462977&rfr_iscdi=true |